Weighted Least Squares Realized Covariation Estimation

Li, Yifan and Nolte, Ingmar and Vasios, Michalis and Voev, Valeri and Xu, Qi (2022) Weighted Least Squares Realized Covariation Estimation. Journal of Banking and Finance, 137: 106420. ISSN 0378-4266

Text (WLS_FINAL)
WLS_FINAL.pdf - Accepted Version
Available under License Creative Commons Attribution-NonCommercial-NoDerivs.
Download (3MB)

Abstract

We introduce a novel weighted least squares approach to estimate daily realized covariation and microstructure noise variance using high-frequency data. We provide an asymptotic theory and conduct a comprehensive Monte Carlo simulation to demonstrate the desirable statistical properties of the new estimator, compared with existing estimators in the literature. Using high-frequency data of 27 DJIA constituting stocks over a period from 2014 to 2020, we confirm that the new estimator performs well in comparison with existing estimators. We also show that the noise variance extracted based on our method can be used to improve volatility forecasting and asset allocation performance.

Item Type:

Journal Article

Journal or Publication Title:

Journal of Banking and Finance

Additional Information:

This is the author’s version of a work that was accepted for publication in Journal of Banking and Finance. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Banking and Finance, 137, 106420, 2022 DOI: 10.1016/j.jbankfin.2022.106420

Uncontrolled Keywords:

/dk/atira/pure/subjectarea/asjc/2000/2003

Subjects:

?? market microstructure noiserealized volatilityrealized covariationweighted least squaresvolatility forecastingasset allocationfinanceeconomics and econometrics ??

Departments:

Lancaster University Management School > Accounting & Finance

ID Code:

164741

Deposited By:

ep_importer_pure

Deposited On:

17 Jan 2022 14:40

Refereed?:

Yes

Published?:

Published

Last Modified:

13 Jan 2024 00:23

URI:

https://eprints.lancs.ac.uk/id/eprint/164741